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A new standard method for creating tabular data views from Fast Healthcare Interoperability Resources (FHIR) addresses challenges in healthcare analytics. This SQL on FHIR approach enhances data accessibility and querying performance for large, complex datasets.

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Area of Science:

  • Health Informatics
  • Data Management
  • Database Systems

Background:

  • Adoption of Fast Healthcare Interoperability Resources (FHIR) in analytics is hindered by complex data structures (JSON/XML) and performance issues with large datasets.
  • Existing solutions for FHIR data transformation and querying are often difficult to implement.
  • Need for a standardized, implementation-agnostic method to facilitate FHIR data analysis.

Purpose of the Study:

  • To develop and validate a new specification for defining views that produce tabular data from FHIR resources.
  • To create an implementation-agnostic method for easier adoption in healthcare analytics.
  • To demonstrate the portability and consistency of the proposed approach across different platforms.

Main Methods:

  • An international working group developed a new specification over 18 months.
  • Multiple independent implementations were developed and tested to validate the specification.
  • The feasibility was evaluated by replicating findings from a prior study using various view runner and database implementations.

Main Results:

  • A standard, implementation-agnostic method for defining SQL on FHIR views was established.
  • These view definitions can be executed across diverse technology platforms.
  • Replication of existing study findings demonstrated the portability and consistency of the approach.

Conclusions:

  • The developed SQL on FHIR view definition method offers a feasible and effective solution to challenges in FHIR analytics.
  • This approach simplifies the transformation of complex FHIR data into a usable tabular format.
  • The demonstrated portability and consistency support broader adoption for improved healthcare data accessibility and analysis.